Dual Hesitant Fuzzy Set based Knowledge and Accuracy Measure with its Application to Power Crisis and Pattern Detection

Fuzzy sets have proven useful in the investigation of unclear phenomena. A number of researchers suggested intuitionistic fuzzy sets (IFSs) and hesitant fuzzy sets (HFSs) as an extension of fuzzy sets (FSs), and these sets have been applied in various contexts. The study of Dual hesitant fuzzy sets contains two type of hesitancy function one is membership and other is non-membership, they carry out the hesitation scenario and provides an adequate way to provide values corresponding to each element present in domain. The FSs, IFSs and HFSs as special cases are all included in the DHFSs. Compared with IFS and HFS, DHFS is more advantageous in dealing with multiple attribute decision making problems. In this paper, a new knowledge and accuracy measure for DHFS has been proposed. The main motive of this paper is to investigate knowledge and accuracy measures for DHFSs and to compare the performance of a proposed knowledge and accuracy measure in the DHF environment with other current measures. We also demonstrate the application of knowledge measure and accuracy measure that we have developed to tackle the problem of power crisis in a developing country. We demonstrate how our suggested accuracy measure of DHFSs outperforms certain similarity and distance measurements.